Machine learning-based classifiers to predict metastasis in colorectal cancer patients

BackgroundThe increasing prevalence of colorectal cancer (CRC) in Iran over the past three decades has made it a key public health burden. This study aimed to predict metastasis in CRC patients using machine learning (ML) approaches in terms of demographic and clinical factors.MethodsThis study focuses on 1,127 CRC patients who underwent appropriate treatments at Taleghani Hospital, a tertiary care facility. The patients were divided into training and test datasets in an 80:20 ratio. Various ML methods, including Naive Bayes (NB), random rorest (RF), support vector machine (SVM), neural network (NN), decision tree (DT), and logistic regression (LR), were used for predicting metastasis in CRC patients. Model performance was evaluated using 5-fold cross-validation, reporting sensitivity, specificity, the area under the curve (AUC), and other indexes.ResultsAmong the 1,127 patients, 183 (16%) had experienced metastasis. In the predictionof metastasis, both the NN and RF algorithms had the highest AUC, while SVM ranked third in both the original and balanced datasets. The NN and RF algorithms achieved the highest AUC (100%), sensitivity (100% and 100%, respectively), and accuracy (99.2% and 99.3%, respectively) on the balanced dataset, followed by the SVM with an AUC of 98.8%, a sensitivity of 97.5%, and an accuracy of 97%. Moreover, lower false negative rate (FNR), false positive rate (FPR), and higher negative predictive value (NPV) can be confirmed by these two methods. The results also showed that all methods exhibited good performance in the test datasets, and the balanced dataset improved the performance of most ML methods. The most important variables for predicting metastasis were the tumor stage, the number of involved lymph nodes, and the treatment type. In a separate analysis of patients with tumor stages I–III, it was identified that tumor grade, tumor size, and tumor stage are the most important features.ConclusionThis study indicated that NN and RF were the best among ML-based approaches for predicting metastasis in CRC patients. Both the tumor stage and the number of involved lymph nodes were considered the most important features

The relationship of air pollution and surrogate markers of endothelial dysfunction in a population-based sample of children

<p>Abstract</p> <p>Background</p> <p>This study aimed to assess the relationship of air pollution and plasma surrogate markers of endothelial dysfunction in the pediatric age group.</p> <p>Methods</p> <p>This cross-sectional study was conducted in 2009-2010 among 125 participants aged 10-18 years. They were randomly selected from different areas of Isfahan city, the second large and air-polluted city in Iran. The association of air pollutants' levels with serum thrombomodulin (TM) and tissue factor (TF) was determined after adjustment for age, gender, anthropometric measures, dietary and physical activity habits.</p> <p>Results</p> <p>Data of 118 participants was complete and was analyzed. The mean age was 12.79 (2.35) years. The mean pollution standards index (PSI) value was at moderate level, the mean particular matter measuring up to 10 μm (PM₁₀) was more than twice the normal level. Multiple linear regression analysis showed that TF had significant relationship with all air pollutants except than carbon monoxide, and TM had significant inverse relationship with ozone. The odds ratio of elevated TF was significantly higher in the upper vs. the lowest quartiles of PM₁₀, ozone and PSI. The corresponding figures were in opposite direction for TM.</p> <p>Conclusions</p> <p>The relationship of air pollutants with endothelial dysfunction and pro-coagulant state can be an important factor in the development of atherosclerosis from early life. This finding should be confirmed in future longitudinal studies. Concerns about the harmful effects of air pollution on children's health should be considered a top priority for public health policy; it should be underscored in primordial and primary prevention of chronic diseases.</p

Molecular Comparison of Three Different Regions of the Genome of Infectious Bronchitis Virus Field Isolates and Vaccine Strains

Abstract Rapid detection and differentiation of infectious bronchitis virus (IBV) involved in the disease outbreak is very important for controlling disease and developing new vaccines. In the present study, three regions of the genome of IBV vaccine and field isolates including S1 gene, gene 3 and nucleocapsid (N) gene along with 3&apos; untranslated region (3&apos; UTR) were amplified and subjected to restriction fragment length polymorphism (RFLP) using three different endonucleases. Amplicons from S1 gene and N-3&apos;UTR generated four RFLP patterns, grouping IBV strains into four similar groups, while amplicons of gene 3 generated three RFLP patterns classifying examined IBVs in different groups from those of S1 and N-3&apos; UTR. 4/91 strain and MNS-7862-1field isolate both belong to 793/B serotype were differentiated from each other based on gene 3, N-3&apos;UTR and S1gene. IBVs belonged to different serotypes showed different RFLP patterns based on RFLP patterns of all three regions. S1 gene and N-3&apos;UTR RFLP analysis differentiated IB88, MNS-7862-1 and 4/91 from each other. This is the first report on the molecular analysis of the gene 3 for IBV strain differentiation. Our results revealed that RFLP analysis of N-3&apos;UTR and S1 gene had the higher discriminatory power than gene 3. None of the RFLP patterns of different regions differentiated 4/91 vaccine strain from its field isolate

Population genetic diversity and structure in Ziziphora tenuior L.: Identification of potential gene pools

Ziziphora tenuior L. is a medicinal plant species of the genus Ziziphora (Labiatae) that grows in different areas of Iran. In order to study the population genetic structure in Ziziphora tenuior, we collected 107 plant specimens from 20 geographical populations that are located in 17 provinces. ISSR molecular markers were used for genetic diversity analysis. The populations studied revealed intra- and inter-population genetic variability. AMOVA test showed significant genetic difference among the studied populations. STRUCTURE plot identified two main gene pools for Ziziphora tenuior in Iran. These populations showed isolation by distance and restrict gene flow occurred among them

Nurse's activities and viewpoints about motivational factors, facilitators, and barriers of patient education

 Patient education is a dynamic and continuous process beginning from patient's admission to discharge and nurses play a vital role in this field. The aim of the study was investigate of Nurse's activities and viewpoints about motivational factors, facilitators, and barriers of patient education in Vasei hospital of Sabzevar in 2016.  This study is a descriptive cross-sectional research. Our research sample include: 111 nurses employed at Vasei hospital of Sabzevar in 2016. Sample was selected by non-random method (easy to access). The data gathering instrument was a questionnaire divided into 5 sections as follows: (1) questions regarding demographic characteristics (2) nursing activities (3) nurses` motivational factors associated with Patient Education (4&amp;5) determining the facilitators and barriers of patient education. Data was analyzed using SPSS (version 20) and descriptive statistics.  Nurses pointed that most of their time is spent for writing tasks such as patient`s situation report (89.2). From nurses� point of view, the most important factor for patient education was job conscience (78.4). They introduced tha

Molecular Comparison of Three Different Regions of the Genome of Infectious Bronchitis Virus Field Isolates and Vaccine Strains

Rapid detection and differentiation of infectious bronchitis virus (IBV) involved in the disease outbreak is very important for controlling disease and developing new vaccines. In the present study, three regions of the genome of IBV vaccine and field isolates including S1 gene, gene 3 and nucleocapsid (N) gene along with 3' untranslated region (3' UTR) were amplified and subjected to restriction fragment length polymorphism (RFLP) using three different endonucleases. Amplicons from S1 gene and N-3’UTR generated four RFLP patterns, grouping IBV strains into four similar groups, while amplicons of gene 3 generated three RFLP patterns classifying examined IBVs in different groups from those of S1 and N-3' UTR. 4/91 strain and MNS-7862-1field isolate both belong to 793/B serotype were differentiated from each other based on gene 3, N-3’UTR and S1gene. IBVs belonged to different serotypes showed different RFLP patterns based on RFLP patterns of all three regions. S1 gene and N-3’UTR RFLP analysis differentiated IB88, MNS-7862-1 and 4/91 from each other. This is the first report on the molecular analysis of the gene 3 for IBV strain differentiation. Our results revealed that RFLP analysis of N-3’UTR and S1 gene had the higher discriminatory power than gene 3. None of the RFLP patterns of different regions differentiated 4/91 vaccine strain from its field isolate